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Every field has its jargon, and AI has more than its share. The good news: most of these terms describe simple ideas hiding behind intimidating words. Here are 30 key terms explained in plain language, so the next article you read makes a lot more sense.
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The essentials
Keep this as a cheat sheet. You do not need to memorize it.
| Term | Plain meaning |
|---|
| AI (Artificial Intelligence) | Software that can do tasks we'd normally consider "smart," like understanding language or recognizing images. |
| Prompt | What you type to an AI; your instruction or question. |
| LLM (Large Language Model) | The kind of AI behind chatbots; trained on huge amounts of text to predict and generate language. |
| Model | The trained "brain" doing the work. ChatGPT, Gemini and Claude each run on models. |
| Token | A chunk of text (roughly a word or part of one) that AI processes. Limits are often measured in tokens. |
| Training | The process of teaching a model by showing it enormous amounts of data. |
Talking to AI
Words you will see when people talk about chatting with a model.
| Term | Plain meaning |
|---|
| Prompt engineering | The skill of asking well. See our prompt framework. |
| Context window | How much text the AI can "keep in mind" at once. |
| System prompt | Hidden instructions that shape how an AI behaves. |
| Hallucination | When AI confidently states something false. Always verify — see fact-checking AI. |
| Fine-tuning | Further training a model for a specific purpose. |
| Temperature | A setting controlling how "creative" vs predictable answers are. |
Types of AI tools
The main product types behind the names on our leaderboard.
| Term | Plain meaning |
|---|
| Generative AI | AI that creates content (text, images, audio, video). |
| Chatbot | A conversational AI you message back and forth with. |
| Text-to-image | Makes pictures from descriptions. See image generators explained. |
| Text-to-speech (TTS) | Turns written text into spoken audio. |
| Speech-to-text | Transcribes spoken words into writing. |
| Multimodal | Handles more than one type of input, like text and images together. |
Behind the scenes
Useful if you read a news piece or a product page and hit a wall of jargon.
| Term | Plain meaning |
|---|
| Algorithm | A set of steps a computer follows to solve a problem. |
| Machine learning | Systems that improve by learning from data rather than being explicitly programmed. |
| Neural network | A model design loosely inspired by how brains connect. |
| Parameters | The internal settings a model adjusts during training; more isn't always better. |
| Dataset | The collection of data used to train or test a model. |
| API | A way for other software to plug into an AI tool. |
Things to watch
Safety and hype words that show up in scam pitches as often as in real docs.
| Term | Plain meaning |
|---|
| Bias | Unfair patterns an AI picks up from its training data. |
| Deepfake | Realistic fake images, audio or video made with AI. |
| Prompt injection | A trick to make AI ignore its instructions; a security concern. |
| Open source / open weight | Models anyone can download and run. |
| AGI | Hypothetical AI as capable as a human across most tasks; doesn't exist yet, despite the hype. |
| Agent | An AI set up to take actions and complete multi-step tasks, not just chat. |
Keep this handy as a reference. You don't need to memorize it — just knowing these exist makes the whole AI world feel a lot less intimidating. Ready to put it into practice? Start with our beginner's roadmap.
